MITx Differential Equations starts May 31
mitxonline.mit.eduHey everyone, if you would like to get a grip on differential equations and are willing to put in the work, then you should know that an instructor paced run starts on May 31st. If you know single variable calculus then you're set to jet! Please sign up here:
https://mitxonline.mit.edu/courses/course-v1:MITxT+18.03.1x/
Incidentally, the prerequisite: 18.01x, also starts on May 31.
https://mitxonline.mit.edu/courses/course-v1:MITxT+18.01.1x/
In this sort of situation is the homework graded and the usual? Or is the sign up just so someone can watch the video?
There are homeworks as well as lecture exercises, recitations and a final exam. As far as grading, there is an auto grader that uses sympy on the backend.
Thanks, signing up! :)
It's funny how differential equations just boil down to plain linear algebra when you restrict yourself to the discrete time domain setting. I feel like courses like this should lead with that to save time for people who will primarily handle them inside computers.
I took a traditional differential equation course, and a separate linear algebra course. Loved both of them.
Do you know any course/book to connect this two courses?
Strang has one although it kind of buried the lede on the linear algebra in my opinion. Try some of the older DE texts (Coddington) or an older Schaum’s outline
In my college linear algebra was a prereq for diff eq for this reason
“Just”.
I suspect that an MIT course would be more interesting than “here’s the class in one sentence. See you next semester!”
He's not wrong. It just takes a semester or two to get there.
As I recall from a (very) long ago differential equations course at MIT, the intro DiffEQ course was very cookbook and, while necessary for some things like system dynamics, weren't super-interesting. (Not that I was ever very good at math.) I did always think it was cool though that you had "imaginary" i terms and they eventually disappeared and you had a real-world result.
Never took linear algebra but I gather it was embedded in other courses in various guises largely pre-computer.
I always thought that math was super well curated…right up until differential equations. Beautiful calculus and linear algebra, followed by a bag of tricks to solve DEs.
As someone who is better at coding than pen & paper math, I definitely enjoyed seeing a lot more cases where the only practical solution was numerical.
Differential equations are way more involved and broad.
Hey, unrelated: Does anyone know why it seems MITx stopped offering new courses ~5 years ago? I'm still bummed out and check their page a few times a year.
(I can vouch for this class and the 2x2 one btw; great stuff; I'd recommend any of their math and science courses. The QM ones are especially good)
Well, the multivariable calculus series was released more recently. Work is ongoing for the 3rd part of that series.
Are there any interesting modern applications of diff. equations in computer science outside physics simulators, and 3d vision? Or some adjacent areas that would benefit from skillset of working with diff. equations?
Optimization by gradient descent is used to do the learning in deep learning. For example, diff eqs are used to create optimizers that improve upon the classic 'adam' say, such as the new 'sophia' [1]. 1. https://arxiv.org/abs/2305.14342
This seems like an ad. I assumed the course would be free, but it is $100.
You can sign up for free. The paid option offers a certificate. That seems to be the only difference.
I guess it's $100 for a bunch of videos of lecturer scratching on a whiteboard something that you can learn yourself with interactive demos, sympy and a jupiter notebook.
Any recommendations about a good set of tutorial notebooks based on sympy?
I found a couple of tutorials, but they're about using sympy rather than the theory, and they aren't actually notebooks:
https://www.sympy.org/scipy-2017-codegen-tutorial/notebooks/...
https://www.cfm.brown.edu/people/dobrush/am33/SymPy/index.ht...
The difference is that there are also a bunch of other people learning the same thing at the same time. Peer pressure as well as due dates helps people stay on track, and there is support on the forum in case you get stuck, or just want to talk about something cool you found related to differential equations or math.
lol isn't that any course? sure cheaper than full tuition
Are we signing up as a group and going to form a discussion somewhere?
I've wanted to redo differential equations so I could buy an Analog Thing...
Hi, there is a integrated discussion forum with latex support.